1. Field of the Disclosure
The present disclosure relates to a method of operating a satellite navigation receiver estimating its position by means of a multiplicity of signals each transmitted by another satellite as ranging source.
2. Discussion of the Background Art
In anticipation of the future Global Navigation Satellite Systems (GNSS) constellations like GPS IIF/III (USA), Galileo (Europe), GLONASS (Russia), and Compass (China) becoming operational, a multitude of questions on the use of these numerous ranging sources will arise. Simulations show that with full Galileo and GPS constellations an average of 18 satellites and a minimum of 13 will be in view for most users. Hence, with the given threat models, the applicability of Receiver Autonomous Integrity Monitoring (RAIM) techniques for the purpose of monitoring position integrity will be increased. Additionally, the use of dual frequency receivers will eliminate almost completely the largest magnitude errors for unaided GPS, those caused by the ionospheric delay.
Unfortunately, one cannot assume that GNSS services different from GPS will have the same satellite failure probabilities which makes it to today's most important integrity threat. A failure probability of 10−3 might be proven and realized by the control segment much more easily than the currently accepted probability of 10−5. Altogether, it will no longer be possible to assume that the probability of failure for more than one satellite within a certain timeframe is negligible.
Further, it is questionable if it is always reasonable to compute a position estimate based on all satellites in view rather than selecting only a subset of the “best”. In Augmented GPS scenarios like the Local Area Augmentation System (LAAS), it could be necessary to consider and correct only a subset of the current constellation, for reasons related to the available signal bandwidth or due to large propagation errors affecting a number of satellite signals.
WO 2007/064250 A1 describes a method of operating a receiver for satellite navigation. Said method comprises selecting a set of preferred signal sources from a group of potential satellite signal sources, receiving signals from the selected set of signal sources, and producing position/time related data based on the received signals. Said method further comprises estimating a respective processing demand required to produce the position/time related data based on each subset of a number of candidate subsets of signal sources among the group of potential signal sources, each candidate subset containing at least a minimum number of signal sources necessary to produce the position/time related data of a desired quality, and selecting the set of preferred signal sources based on a candidate subset being associated with a lowest estimated processing demand during a subsequent operating period for the receiver. The processing demand may be estimated by estimating a respective signal quality of each signal in the group of potential signal sources. The signal quality may be reflected by signal power parameter estimation and/or noise density parameter estimation and/or pseudorange error parameter estimation and/or parameter indicating interference detection, and/or signal source health/status data.
The Multiple Hypothesis Solution Separation (MHSS) technique, described in Pervan Boris S., Pullen Samuel P. and Christie Jock R.: “A Multiple Hypothesis Approach to Satellite Navigation Integrity”, Journal of The Intitute of Navigation, 1998, Vol. 45, pp. 61-71, is one of the most advanced existing approaches to identify faulty satellites by observing their influences on the Vertical Protection Level (VPL). This RAIM technique separates the computation of the VPL in multiple hypotheses, which include the cases where single and multiple satellites or even whole constellations have failed. By determining the individual VPL values under each of the hypotheses, weighted by the probability of their occurrence, one can determine the overall VPL. In order to identify faulty satellites, the algorithm builds subsets of the current geometry by excluding one or multiple satellites at a time. An overall VPL is computed for each subset and, as the VPL should increase with a decreasing number of correct satellites, one can expect that the VPL values for the subsets are all higher than for the full geometry. Nevertheless, if a satellite bias influenced the position estimation by a considerable extent, the computed VPL will decrease when excluding this faulty satellite. Therefore, the satellite that was excluded in the corresponding subset, which results in the lowest VPL, is assumed to be the faulty one. By minimizing the VPL, satellites with a high ranging bias which do not translate in a large position domain error may not be excluded, as their contribution still reduces the VPL, even though to a small extent.
Lee Young C.: “Analysis of Range and Position Comparison Methods as a Means to Provide GPS Integrity in the User Reciever”, Annual Meeting of the Insitute of Navigation, Seattle, 1986, pp. 1-4 describes a Range Comparison Method, in which the user receiver first estimates user position and clock bias based on four satellites at a time where an overall of five satellites were assumed. Each of the five 4-satellite navigation solutions is then used to predict the pseudorange to the fifth satellite not included in that particular solution. The differences between predicted pseudoranges and the corresponding measured pseudoranges are used as the basis for detecting an abnormal state. Since only a single linear equation is provided for a hypothesis test, this method can only detect an abnormal state where the error in user position estimate exceeds a threshold; it is not possible to identify any bad satellite(s), using only five satellites.
In contrary to the new procedure, existing techniques use the general approach to identify failures by measuring the level of integrity. One assumes that a satellite signal that does not degrade the integrity should not be excluded from the position estimation. This is for instance the case in the mentioned MHSS technique, which uses the VPL as a measure of integrity. Due to the weighted position solution, even a satellite signal with high ranging bias does not necessarily translate into a large position domain error and can still reduce the overall VPL, even though to a small extent. Hence, in these scenarios the faulty or biased signal is not detected at all. However, the influence of satellite signals to the position estimation can change abruptly (especially in urban canyons) and no prior knowledge about faulty signals is available. Further, with multiple constellations present, one might want to exclude the failed satellite, for instance to improve the accuracy, even if this does not always result in the minimum VPL value, as long as the protection level stays below the Vertical Alert Limit VAL (=upper bound of the VPL).
But also in the scenarios where the most important signal with respect to the position estimation (the one with the highest influence) has a failure, known approaches still need relatively high biases to identify this signal. However, it is of high importance to detect faulty signals already at low biases to allow timely warnings to the user of the receiver.
As already indicated, multiple satellite failures at a time can no longer be neglected with the rise of new GNSS services and the resulting increase of available ranging sources.
It is an object of the present disclosure to originate techniques, which are capable of handling these new requirements, and reliably detect and exclude multiple biased satellite signals at a time.
Another object of the present disclosure is to present a new procedure which is capable of detecting and identifying all satellite signals with a bias higher than a given threshold to pave the way for safety critical and mass-market applications by allowing reliable and accurate estimations of position, velocity, and time at the receiver even during erroneous satellite constellations. Further on, not only the integrity but also the precision of the estimations are to be improved significantly by excluding faulty satellite signals at low biases. With a good estimate of the current ranging bias of each individual satellite, it is possible to reduce also multipath effects by eliminating the common bias.